File size: 2,332 Bytes
2dd7160
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
60c555f
2dd7160
 
 
 
 
 
 
 
 
 
 
f55372e
6ce4b91
 
2dd7160
60c555f
2dd7160
 
 
 
 
 
 
 
 
 
 
f55372e
 
5d43c4a
6ce4b91
 
 
 
 
 
 
 
 
 
5d43c4a
6ce4b91
 
f8b1478
fb85cfd
 
f8b1478
850db28
603d210
 
 
60f8c26
2dd7160
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
import warnings
import gradio as gr
from transformers import pipeline
import io, base64
from PIL import Image
import numpy as np
import tensorflow as tf
import mediapy
import os
import sys
from huggingface_hub import snapshot_download

#CREDIT: this demo is based *heavily* on https://huggingface.co/spaces/osanseviero/latent-video

with warnings.catch_warnings():
  warnings.simplefilter('ignore')
  image_gen = gr.Interface.load("spaces/multimodalart/latentdiffusion")

  os.system("git clone https://github.com/google-research/frame-interpolation")
  sys.path.append("frame-interpolation")
  from eval import interpolator, util
  
ffmpeg_path = util.get_ffmpeg_path()
mediapy.set_ffmpeg(ffmpeg_path)

model = snapshot_download(repo_id="akhaliq/frame-interpolation-film-style")
interpolator = interpolator.Interpolator(model, None)


def generate_images(text, width=256, height=256, steps=50, num_images=2,
                    diversity=4):

    image_bytes = image_gen(text, steps, width, height, num_images, diversity)
    
    # Algo from spaces/Gradio-Blocks/latent_gpt2_story/blob/main/app.py
    generated_images = []
    for image in image_bytes[1]:
        image_str = image[0]
        image_str = image_str.replace("data:image/png;base64,","")
        decoded_bytes = base64.decodebytes(bytes(image_str, "utf-8"))
        img = Image.open(io.BytesIO(decoded_bytes))
        generated_images.append(img)
        
    return generated_images


def generate_interpolation(text, fps=7, steps=4):    
  images = []
  frames = []
  for i, t in enumerate(text.split(', ')):
    print(f'image {i}: {t.lower().strip()}', end='...')
    images.extend(generate_images(t.lower().strip()))
    print('done!')
  
    frames.append(f'frame_{i}.png')
    images[-1].save(frames[-1])

  vid = list(util.interpolate_recursively_from_files(frames, steps, interpolator))
  mediapy.write_video("out.mp4", vid, fps=fps)
  return "out.mp4"

demo = gr.Blocks()

with demo:
  text = gr.Textbox(placeholder='human, human brain, brain in a computer, humanoid robot', label='Input a comma-separated list of terms or (brief) descriptions:')
  button = gr.Button("Generate Video")
  output = gr.Video(label="Generated Video")
        
  button.click(fn=generate_interpolation, inputs=text, outputs=output)  

demo.launch(debug=True, enable_queue=True)